Estimation and Impact of Nonuniform Horizontal Correlation Length Scales for Global Ocean Physical Analyses

Optimally modeling background-error horizontal correlations is crucial in ocean data assimilation. This paper investigates the impact of releasing the assumption of uniform background-error correlations in a global ocean variational analysis system. Spatially varying horizontal correlations are introduced in the recursive filter operator, which is used for modeling horizontal covariances in the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) analysis system. The horizontal correlation length scales (HCLSs) were defined on the full three-dimensional model space and computed from both a dataset of monthly anomalies with respect to the monthly climatology and through the so-called National Meteorological Center (NMC) method. Different formulas for estimating the correlation length scale are also discussed and applied to the two forecast error datasets. The new formulation is tested within a 12-yr period (2000–11) in the ½° resolution system. The comparison with the data assimilation system using uniform background-error horizontal correlations indicates the superiority of the former, especially in eddy-dominated areas. Verification skill scores report a significant reduction of RMSE, and the use of nonuniform length scales improves the representation of the eddy kinetic energy at midlatitudes, suggesting that uniform, latitude, or Rossby radius-dependent formulations are insufficient to represent the geographical variations of the background-error correlations. Furthermore, a small tuning of the globally uniform value of the length scale was found to have a small impact on the analysis system. The use of either anomalies or NMC-derived correlation length scales also has a marginal effect with respect to the use of nonuniform HCLSs. On the other hand, the application of overestimated length scales has proved to be detrimental to the analysis system in all areas and for all parameters

Forecast and analysis assessment through skill scores

International audienceThis paper describes a first comprehensive evaluation of the quality of the ten days ocean forecasts produced by the Mediterranean ocean Forecasting System (MFS). Once a week ten days forecasts are produced. The forecast starts on Tuesday at noon and the prediction is released on Wednesday morning with less then 24 hr delay. In this work we have considered 22 ten days forecasts produced from the 16 August 2005 to the 10 January 2006. All the statistical scores have been done for the Mediterranean basin and for 13 regions in which the Mediterranean sea has been subdivided. The forecast evaluation is given here in terms of root mean square (rms) values. The main skill score is computed as the root mean square of the difference between forecast and analysis (FA) and forecast and persistence (FP), where the persistence is defined as the average of the day of the analysis corresponding to the first day of the forecast. A second skill score (SSP) is defined as the ratio between rms of FA and FP, giving the percentage of accuracy of the forecast with respect to the persistence (Murphy 1993). The rms of FA is always better than FP and the FP rms error is double than the rms of FA. It is found that in the surface layers the error growth is controlled mainly by the atmospheric forcing inaccuracies while at depth the forecast errors could be due to adjustments of the data assimilation scheme to the data insertion procedure. The predictability limit for our ocean forecast seems to be 5?6 days connected to atmospheric forcing inaccuracies and to the data availability for assimilation

Validation and intercomparison of two vertical-mixing schemes in the Mediterranean Sea

International audienceIn this study, two types of vertical turbulence closure models are tested in the Mediterranean Sea in a one-dimensional configuration. The numerical experiments are performed at different locations in the Mediterranean for which the year 2004 is simulated. The model results are then compared and validated with in-situ temperature observations. For the model simulations, initial profiles of temperature and salinity come from the ARGO (Array for Real-time Geostrophic Oceanography) profiles. The surface forcing (momentum, heat) is calculated from bulk formulae using 6-hourly atmospheric data from the European Center for Medium Range Weather Forecast (ECMWF). The vertical mixing schemes tested in this study are a second-order statistical model (k-?) and the non-local K-profile parameterization (KPP). Both schemes yield similar results in terms of reproducing the water column dynamics. A major source of discrepancy between model and observations comes from the uncertainties in the atmospheric forcing parameterization. At this point, net shortwave radiation data from NCEP atmospheric reanalysis has been used obtaining a more realistic Sea Surface Temperature (SST) compared with satellite observations for the summer months

A Revised Scheme to Compute Horizontal Covariances in an Oceanographic 3D-VAR Assimilation System.

We propose an improvement of an oceanographic three dimensional variational assimilation scheme (3D-VAR), named OceanVar, by introducing a recursive filter (RF) with the third order of accuracy (3rd-RF), instead of an RFwith first order of accuracy (1st-RF), to approximate horizontal Gaussian covariances. An advantage of the proposed scheme is that the CPU's time can be substantially reduced with benefits on the large scale applications. Experiments estimating the impact of 3rd-RF are performed by assimilating oceanographic data in two realistic oceanographic applications. The results evince benefits in terms of assimilation process computational time, accuracy of the Gaussian correlation modeling, and show that the 3rd-RF is a suitable tool for operational data assimilation

Ionian Sea circulation as clarified by assimilation of glider observations

Glider observations of temperature and salinity in the Ionian Sea (Eastern Mediterranean Sea), made in the period October 2004-December 2004, were assimilated into an operational forecasting model together with other in-situ and satellite observations. The impact of glider data on the estimation of the circulation is studied and it is found that the assimilation of glider data significantly improve the vertical structure of temperature and salinity fields and remove biases. The accurate representation of the dynamical structures due to the assimilation of glider data allowed a detailed analysis of the dynamics of the Atlantic Ionian Stream (AIS). During autumn and in the Sicily Strait, the AIS is strengthened by the positive but weak wind stress curl near the southern Sicilian coast and by the temperature gradient between the warm surface mixed layer and the cold upwelled waters near Sicily. In winter the change of position of the wind stress curl zero line and the cooling of the surface mixed layer forces the AIS to shift southward in the Ionian Sea. The AIS is shown for the first time to pinch off an eddy in the Ionian Sea

A high resolution free surface model of the Mediterranean Sea

International audienceThis study describes a new model implementation for the Mediterranean Sea which has the presently highest vertical resolution over the Mediterranean basin. The resolution is of 1/16°×1/16° in horizontal and 71 unevenly spaced vertical levels. This model has been developed in the frame of the EU-MFSTEP project and it is the operational forecast model presently used at the basin scale. For the first time in the Mediterranean, the model considers an implicit free surface and this characteristics enhances the model capability to simulate the sea surface height variability. In this study we show the calibration/validation experiments done before and after the model has been used for forecasting. The first experiment consist of six years of a simulation forced by a perpetual year forcing and the other experiment is a simulation from January 1997 to December 2004, forcing the model with 6 h atmospheric forcing fields from ECMWF. For the first time the model Sea Level Anomaly is compared with SLA and with ARGO data to provide evidence of the quality of the simulation. The results show that this model is capable to reproduce most of the variability of the general circulation in the Mediterranean Sea even if some basic model inadequacies stand out and should be corrected in the near future

Impact of data assimilation of glider observations in the Ionian Sea (Eastern Mediterranean)

Glider observations of temperature, salinity and vertically averaged velocity in the Ionian Sea (Eastern Mediterranean Sea), made in the period October 2004 - December 2004, were assimilated into an operational forecasting model together with other in-situ and satellite observations. The study area has a high spatial and temporal variability of near-surface dynamics, characterized by the entrance of the Atlantic Ionian Stream (AIS) into the Northern Ionian Sea. The impact of glider observations on the estimation of the circulation is studied, and it is found that their assimilation locally improves the prediction of temperature, salinity, velocity and surface elevation fields. However, only the assimilation of temperature and salinity together with the vertically averaged velocity improves the forecast of all observed parameters. It is also found that glider observations rapidly impact the analyses even remotely, and the remote impacts on the analyses remain several months after the presence of the glider. The study emphasizes the importance of assimilating as much as possible all available information from gliders, especially in dynamically complex areas

Impact of Multi-altimeter Sea Level Assimilation in the Mediterranean Forecasting Model

In this paper we analyze the impact of multi-satellite altimeter observations assimilation in a high-resolution Mediterranean model. Four different altimeter missions (Jason-1, Envisat, Topex/Poseidon interleaved and Geosat Follow-On) are used over a 7-month period [September 2004, March 2005] to study the impact of the assimilation of one to four satellites on the analyses quality. The study highlights three important results. First, it shows the positive impact of the altimeter data on the analyses. The corrected fields capture missing structures of the circulation and eddies are modified in shape, position and intensity with respect to the model simulation. Secondly, the study demonstrates the improvement in the analyses induced by each satellite. The impact of the addition of a second satellite is almost equivalent to the improvement given by the introduction of the first satellite: the second satellite data brings a 12% reduction of the root mean square of the differences between analyses and observations for the Sea Level Anomaly (SLA). The third and fourth satellite also significantly improve the rms, with more than 3% reduction for each of them. Finally, it is shown that Envisat and Geosat Follow-On additions to J1 impact the analyses more than the addition of Topex/Poseidon suggesting that the across track spatial resolution is still one of the important aspects of a multi-mission satellite observing system. This result could support the concept of multi-mission altimetric monitoring done by complementary horizontal resolution satellite orbits

Forecast and analysis assessment through skill scores

This paper describes a first comprehensive evaluation of the quality of the ten days ocean forecasts produced by the Mediterranean ocean Forecasting System (MFS). Once a week ten days forecasts are produced. The forecast starts on Tuesday at noon and the prediction is released on Wednesday morning with less then 24 hr delay. 5 In this work we have considered 22 ten days forecasts produced from the 16 August 2005 to the 10 January 2006. All the statistical scores have been done for the Mediterranean basin and for 13 regions in which the Mediterranean sea has been subdivided. The forecast evaluation is given here in terms of root mean square (rms) values. 10 The main skill score is computed as the root mean square of the difference between forecast and analysis (FA) and forecast and persistence (FP), where the persistence is defined as the average of the day of the analysis corresponding to the first day of the forecast. A second skill score (SSP) is defined as the ratio between rms of FA and FP, giving the percentage of accuracy of the forecast with respect to the persistence 15 (Murphy 1993). The rms of FA is always better than FP and the FP rms error is double than the rms of FA. It is found that in the surface layers the error growth is controlled mainly by the atmospheric forcing inaccuracies while at depth the forecast errors could be due to adjustments of the data assimilation scheme to the data insertion procedure. The pre20 dictability limit for our ocean forecast seems to be 5–6 days connected to atmospheric forcing inaccuracies and to the data availability for assimilation

Very large ensemble ocean forecasting experiment using the Grid computing infrastructure

Atmospheric and oceanic ensemble forecasting is a way to deal with uncertainty related to inaccurate knowledge of the initial state of the atmosphere and the ocean, the lateral and vertical boundary condition errors and the model physics shortfalls (Lewis, 2005, Epstein, 1969). Since the atmosphere and the ocean are extremely non-linear systems (Lorenz, 1993, Saravanan et al., 2000) initial uncertainties can amplify and limit the predictability of short term forecasts (Kleeman and Majda, 2005). For the ocean, ensemble forecasting is a novel field. Ensemble methods are used to compute the background error covariance matrix in data assimilation schemes (Evensen, 2003) but are not used yet to quantify the forecast uncertainty in short term ocean forecasting systems. Initial conditions uncertainty is a major source of unpredictability for ocean currents due to the limited observations available for nowcasting and the highly non-linear physics. In this study we explore the short term ensemble forecast variance generated by perturbing the initial conditions using a new computational facility, so-called Grid infrastructure (http://grid.infn.it/), distributed over the Italian territory. This infrastructure allowed us to perform several ensemble forecast experiments with 1000 members: they are completed within 5 hours of wall-clock time after their submission and the ensemble variance peaks at the mesoscales